Search Results (102)

Wildfires increasingly threaten Mediterranean landscapes, particularly in regions like Attica, Greece, where urban sprawl, agricultural abandonment, and climatic conditions heighten the risk at the Wildland–Urban Interface (WUI). The Mediterranean basin, recognized as one of the global wildfire “hotspots”, has witnessed a steady increase in both fire severity, frequency, and burned area during the last four decades, a trend amplified by urban sprawl and agricultural land abandonment. This study represents the first integrated, region-wide mapping of the WUI and associated wildfire risk in Attica, the most densely urbanized area in Greece and one of the most fire-exposed metropolitan regions in Southern Europe, utilizing advanced techniques such as Earth Observation and GIS analysis. For this purpose, various geospatial datasets were coupled, including Copernicus High Resolution Layers, multi-decadal Landsat fire history archive, UCR-STAR building footprints, and CORINE Land Cover, among others. The research delineated WUI zones into 40 interface and intermix categories, revealing that WUI encompasses 26.29% of Attica, predominantly in shrub-dominated areas. An analysis of fire frequency history from 1983 to 2023 indicated that approximately 102,366 hectares have been affected by wildfires. Risk assessments indicate that moderate hazard zones are most prevalent, covering 36.85% of the region, while approximately 25% of Attica is classified as moderate, high, or very high susceptibility zones. The integrated risk map indicates that 37.74% of Attica is situated in high- and very high-risk zones, principally concentrated in peri-urban areas. These findings underscore Attica’s designation as one of the most fire-prone metropolitan regions in Southern Europe and offer a viable methodology for enhancing land-use planning, fuel management, and civil protection efforts. Full article

This paper presents the design, development, and field testing of an Operational Fire Management System (OFMS) aimed at enhancing situational awareness and improving the safety and efficiency of firefighting operations. The system integrates real-time intelligence and remote monitoring to provide emergency management personnel and first responders with accurate information on vehicle location, communication status, and water level monitoring. Developed in collaboration with the Australian Capital Territory Rural Fire Service (ACT RFS), the OFMS prototype encompasses three core subsystems: the Monitoring and Environmental Sensing Subsystem (MESS), the Communication and Vital Monitoring Subsystem (CVMS), and the Command-and-Control Interface Subsystem (CCIS). MESS introduces a tilt-compensated ultrasonic algorithm for accurate water level estimation in moving fire trucks, CVMS leverages an open-source smartwatch with LoRa communication for real-time physiological tracking, and CCIS offers a cloud-based interface for live visualisation and coordination. Together, these subsystems form a practical and scalable framework for supporting frontline operations, particularly in rural firefighting contexts where vehicles are required to operate off-road and deliver large volumes of water to isolated locations. By providing real-time visibility of resource availability and crew status, the system strengthens operational coordination and decision-making in environments where connectivity is often limited. This paper discusses the design and implementation of the prototype, highlights key performance results, and outlines opportunities for future development, including improved environmental resilience, expanded sensor integration, and multi-agency interoperability. The findings confirm that the OFMS represents a novel and field-ready approach to fireground management, empowering firefighting teams to respond more effectively to emergencies and better protect lives, property, and the environment. Full article

The present article focuses on the assessment of the potential advantages and disadvantages of the utilisation of modern building inventory technologies in crisis situations, using a case study of Ukraine, currently engulfed in armed conflict. The following methods are described in detail: laser scanning, 360-degree camera images, and photo series. The authors conducted an in-depth SWOT/TOWS analysis, adapted to the specifics of the post-conflict environment, with a view to the future reconstruction of damaged buildings. The originality of the study lies in the use of a modified, quantitative version of the conventional SWOT analysis, supplemented with a weighting and rating system, which allowed for a more accurate assessment of the effectiveness of various technologies, including laser scanning. While the study focuses on the Ukrainian context, the authors emphasise that the developed methodology is universal and can be successfully applied to other critical areas, such as regions affected by earthquakes, floods, fires, or technological disasters. A modified SWOT/TOWS analysis can serve as a valuable tool in crisis management and infrastructure reconstruction during emergencies, providing the data necessary for making rational and effective decisions regarding the use of modern technologies in construction. The analysis revealed that, of the analysed inventory strategies, only laser scanning technology fits the so-called “maxi-maxi” strategy, a scenario in which both internal resources and external capabilities are maximised. The remaining two strategies were designated as “maxi-mini,” signifying that their implementation is associated with elevated levels of risk despite their inherent advantages. It is imperative to acknowledge the existence of substantial external threats that persist. Nevertheless, this does not constitute a complete rejection of the concept. This study examines armed conflict as a research context for a selection of buildings in Ukraine. The analysis was constrained to the three most prevalent methods: The use of TLS, SfM, and 360-degree cameras is also a key component of the methodology. Full article

Due to a complex of factors, visually impaired people are facing difficulties and increased risks during fire emergencies and evacuations from different types of buildings. Even if a lot of studies have been conducted to improve the mobility and autonomy of people with visual impairment during emergency evacuation processes, these offer only partial solutions, especially in the presence of uncertainties characteristic of fire evolution. Aiming for a more comprehensive approach to the safe evacuation of people with visual impairments, this paper proposes a support system that integrates innovative aspects related to the architecture of the application, modeling and simulation methods, and experimental realization. The system is decentralized, capable of anticipating possible fire extensions and determining, in real-time, new corresponding evacuation routes. The overall design complies with the standard norms in emergency situations. Two models, one developed in Stateflow and the other based on Delay Time Petri Nets (DTPN), were constructed to describe the dynamic behavior of the system in the presence of unexpected events that can change the initial recommended evacuation path. To test the functionality and efficiency of the proposed system, the conditions created by potential fire sources were simulated as a part of realistic scenarios. Tests were conducted with visually impaired people. Simulation and prototype testing showed that the presented system can improve evacuation times, achieving a measurable gain compared to scenarios where there is no information regarding fire evolution. Full article

Forest ecosystems are vital to sustainable development, contributing to economic, environmental and social well-being. However, the increasing frequency and severity of wildfires threaten these ecosystems, demanding more effective and integrated fire management (IFM) strategies. Current suppression efforts face limitations due to high resource demands and the need for timely, informed decision-making under uncertain conditions. This paper presents the SILVANUS project’s approach to developing an advanced Decision Support System (DSS) designed to assist incident commanders in optimizing resource allocation during wildfire events. Leveraging Geographic Information Systems (GIS), real-time data collection, AI-enhanced analytics and multicriteria optimization algorithms, the SILVANUS DSS component integrates diverse data sources to support dynamic, risk-informed decisions. The system operates within a cloud-edge infrastructure to ensure scalability, interoperability and secure data management. We detail the formalization of the resource allocation problem, describe the implementation of the DSS within the SILVANUS platform, and evaluate its performance in both controlled simulations and real-world pilot scenarios. The results demonstrate the system’s potential to enhance situational awareness and improve the effectiveness of wildfire response operations. Full article

This study constructs a comprehensive analytical framework for fire evacuation efficiency in high-rise buildings based on risk management theory, environment–behavior relationship theory, and stress-cognition theory. Through a systematic literature review and three rounds of Delphi expert consultation, a measurement questionnaire for fire-escape behavior was developed, ultimately screening out 35 key measurement items. Data were collected from 248 residents of high-rise residential buildings in Beijing who had experienced fires. Exploratory factor analysis (EFA), confirmatory factor analysis (CFA), and structural equation modeling (SEM) were employed to validate the model. The results show that the fire emergency management system (FEMS) and building-safety performance planning (BSPP) have a significant positive impact on escape response behavior (ERB), while situational panic psychological perception (SPPP) has a negative impact. The study also finds that emergency-response training and diversified escape-route design are key driving factors, and cognitive bias significantly affects situational panic psychological perception. This research provides empirical support for fire-escape management in high-rise buildings and develops a reliable measurement tool. Full article

This study evaluates the competency-based performance of Initial Incident Commander (IIC) candidates—fire officers who serve as first-arriving, on-scene incident commanders—in South Korea and identifies sub-competency deficits to inform training improvements. Using evaluation data from 92 candidates tested between 2022 and 2024—of whom 67 achieved certification and 25 did not—we analyzed counts and mean scores for each sub-competency and integrated transcribed radio communications to contextualize deficiencies. Results show that while a majority (72.8%) passed, a significant proportion (27.2%) failed, with recurrent weaknesses in crisis response, progress management, and decision-making. For example, “Responding to Unexpected or Crisis Situations 3-3” recorded 27 unsuccessful cases with a mean score of 68.8. Candidates also struggled with resource allocation, situational awareness and radio communications. The study extends recognition-primed decision-making theory by operationalizing behavioral marker frameworks and underscores the need for predetermined internal alignment, scalability and teamwork synergy. Practical implications recommend incorporating high-fidelity simulation and VR scenarios, competency frameworks and reflective debriefs in training programs. Limitations include the single-country sample, reliance on predetermined scoring rubrics and absence of team-level analysis. Future research is indispensable to adopt multi-jurisdictional longitudinal designs, evaluate varied training interventions, assess skill retention and explore the interplay between physical and cognitive training over time. Full article

Designing fire evacuation strategies for hospitals involves navigating complex infrastructure and accommodating the unique needs of patients, many of whom may have limited mobility or require specialized support during emergencies. This study examines critical egress parameters and their impact on evacuation efficiency in hospital environments, emphasizing configurations that can improve safety and reduce evacuation time. Although the inclusion of smoke effects in recent evacuation models is gaining traction, their combined impact with assisted evacuation scenarios in hospital settings remains underexplored. By integrating smoke propagation data into evacuation modelling, we analyze the effects of reduced visibility and smoke spread on egress routes and occupant behavior. Findings show that smoke effects significantly increase evacuation time estimates (around 50%) compared to traditional models (without accounting for smoke effects), highlighting the risk of underestimation in practical applications, particularly in regions where strict codal compliance is lacking. The study also reveals that stairway width, number, and location substantially affect evacuation times, with about 40% reduction achieved by increasing stairway width from 44 to 66 inches. Additionally, situational awareness enhancements, such as real-time information on fire location and safe exits, can improve evacuation efficiency by about 35%. For taller hospital buildings, the findings highlight the need for implementation of situational awareness in addition to optimized egress planning to achieve safe and efficient evacuation strategies. Full article

When a building normally used for exhibitions is converted into a Fangcang shelter hospital in emergency situations, its original space combination, functional flow line, and safety exits are significantly changed. When the building becomes densely populated, if an accident such as a fire, explosion, or earthquake occurs, then safe evacuation will be a serious challenge. This study systematically considers the characteristics of the building space and functional flow line after the conversion of an exhibition building to a Fangcang shelter hospital. Pathfinder software was used to simulate representative scenarios of a Fangcang shelter hospital and to analyze the main spatial factors affecting evacuation efficiency in terms of evacuation time, spatial congestion characteristics, and the exits used by personnel. Then, a targeted design optimization strategy was proposed based on the accessibility of safety exits and the internal space layout of the building. Finally, a simulation was used to verify the effectiveness of the design strategy. The results of this study provide solid theoretical support and methodological guidance for the spatial arrangement of exhibition buildings converted into Fangcang shelter hospitals so as to effectively improve the efficiency of safe evacuation and promote the resilience and safety of exhibition buildings. Full article

The continuous advancement of fire protection technologies has necessitated the development of comprehensive safety standards, leading to an increasingly diversified and specialized regulatory landscape. This has made it difficult for fire protection professionals to quickly and accurately locate the required fire safety standard information. In addition, the lack of effective integration and knowledge organization concerning fire safety standard entities has led to the severe fragmentation of fire safety standard information and the absence of a comprehensive “one map”. To address this challenge, we introduce FT-FLAT, an innovative CNN–Transformer fusion architecture designed specifically for fire safety standard entity extraction. Unlike traditional methods that rely on rules or single-modality deep learning, our approach integrates TextCNN for local feature extraction and combines it with the Flat-Lattice Transformer for global dependency modeling. The key innovations include the following. (1) Relative Position Embedding (RPE) dynamically encodes the positional relationships between spans in fire safety texts, addressing the limitations of absolute positional encoding in hierarchical structures. (2) The Multi-Branch Prediction Head (MBPH) aggregates the outputs of TextCNN and the Transformer using Einstein summation, enhancing the feature learning capabilities and improving the robustness for domain-specific terminology. (3) Experiments conducted on the newly annotated Fire Safety Standard Entity Recognition Dataset (FSSERD) demonstrate state-of-the-art performance (94.24% accuracy, 83.20% precision). This work provides a scalable solution for constructing fire safety knowledge graphs and supports intelligent information retrieval in emergency situations. Full article

Historical buildings are exposed to an increased risk of fire. The direct influence comes from the buildings’ structural design and the fire protection level. The fundamental principle for reducing the loss of heritage value in historical buildings due to fire is fire protection, as part of crisis management. This article focuses on selected castle buildings from Slovakia. Three castle buildings were selected based on their location in the country. All of them are currently used for museum purposes. Using an analytical form, we assessed fire hazards and fire safety measures in two parts, calculated the fire risk index, and proposed solutions. Qualitative research, which is more suitable for the issue at hand, was used to evaluate the selected objects. The main methods used in the research focused on visual assessment of the current condition of the objects and analysis of fire documentation and its comparison with currently valid legal regulations. Based on the results, we can conclude that Kežmarok Castle (part of the historical city center) has a small fire risk (fire risk index = 13 points). Trenčín Castle (situated on a rock above the city) and Stará Ľubovňa Castle (situated on a limestone hill outside the city, surrounded by forest) have an increased risk of fire (fire risk index = 50–63). Significant risk sources identified included surrounding forest areas, technical failures related to outdated electrical installations, open flames during cultural events, the concentration of highly flammable materials, and complex evacuation routes for both people and museum collections. Full article

The purpose of this research was to indicate the importance of an efficient design of steel frame structures, taking into account the fire design situation. In the case of steel frame structures, the typical mechanisms of failure (sway, beam, and mixed) are well known. Using this knowledge, combined with a reliability assessment of single nodes, may let designers reduce both the amount of material used for a structure and the total cost of the structure. In this article, one-story, single-nave frames with different loads were analyzed. Two types of loads were analyzed: symmetrical and unsymmetrical. Both cases resulted in different failure paths. The static analysis of the structure in the following minutes of the fire duration was carried out in the Robot Structural Analysis programme. The temperature load was computed according to the Eurocode recommendation with the assumption that the temperature of fire gases is described by the standard fire curve. Afterward, the system reliability analysis for the selected failure paths was conducted. Additionally, the displacement analysis was performed in the following minutes of the fire. The biggest challenge in the proposed method is that there are many potential failure paths, and checking all of them is very time-consuming, even when using advanced computers. Therefore, only selected collapse modes were analyzed. Full article

Early fire detection plays a crucial role in minimizing harm to human life, buildings, and the environment. Traditional fire detection systems struggle with detection in dynamic or complex situations due to slow response and false alarms. Conventional systems are based on smoke, heat, and gas sensors, which often trigger alarms when a fire is in full swing. In order to overcome this, a promising approach is the development of memristor-based gas sensors, known as gasistors, which offer a lightweight design, fast response/recovery, and efficient miniaturization. Recent studies on gasistor-based sensors have demonstrated ultrafast response times as low as 1–2 s, with detection limits reaching sub-ppm levels for gases such as CO, NH₃, and NO₂. Enhanced designs incorporating memristive switching and 2D materials have achieved a sensitivity exceeding 90% and stable operation across a wide temperature range (room temperature to 250 °C). This review highlights key factors in early fire detection, focusing on advanced sensors and their integration with IoT for faster, and more reliable alerts. Here, we introduce gasistor technology, which shows high sensitivity to fire-related gases and operates through conduction filament (CF) mechanisms, enabling its low power consumption, compact size, and rapid recovery. When integrated with machine learning and artificial intelligence, this technology offers a promising direction for future advancements in next-generation early fire detection systems. Full article

There is currently a growing need for energy, which, combined with climate change, has increased the focus on renewable energies. Among them, biomass energy takes the lion’s share, and this can create forestry pressures or lead to the excessive consumption of resources. To mitigate this situation, residual biomass from agroforestry has emerged as a valuable resource, supporting energy transition and mitigating these challenges. However, this biomass is traditionally burned, leading to large fires, as a result of the high logistical costs associated with the lack of information/coordination between those involved in the chain. Therefore, the primary objective of this work is to address this gap by presenting an information management model based on a web application, which aims to increase transparency, integrate stakeholders, and improve logistical decisions. In methodological terms, this study follows the principles of human-centered design, as well as an agile software development methodology. The results include the creation of a new, flexible information management ecosystem, which allows each stakeholder to take on different roles according to their needs in the chain. In addition, lean information management principles have been included in order to reduce waste in information content and flow. Full article

The interaction mechanism of multi-physical fields in a 330 MW tangentially fired boiler is explored by coupling the CFD (computational fluid dynamics) model and the working fluid side hydrodynamic model under steady-state conditions. The research focuses on the flue gas flow field, the hydrodynamic safety of the water wall, the variation of the working fluid parameters and the formation and distribution characteristics of sulfide (SO₂, H₂S) under different steady loads (35%, 50%, 75%, 100% Boiler Maximum Continuous Rating). The results show that under high load, the flue gas attaches to the wall. The overall stagnation differential pressure ratio (1.85–2.07) and reversal differential pressure ratio (1.22–1.30) of the G1 tube group with the lowest heat flux are higher than the safety threshold (1.05), proving reliable operational safety under equilibrium conditions. The temperature distribution of the furnace center obtained by numerical simulation is consistent with the actual situation. The mass fraction of sulfide increases significantly with the increase in load. SO₂ is mainly distributed in the wall area of the middle and upper burners, while H₂S is mainly distributed in the wall area between the secondary air and the main burner. The maximum mass fractions of SO₂ and H₂S at 330 MW are 0.120% and 0.0524%, respectively. It is suggested that a wall-attached air system be added to inhibit the enrichment of corrosive gases. This work may provide theoretical support and engineering guidance for multi-objective optimization design and high temperature corrosion prevention and control of tangentially fired boilers. Full article